Abstract / truncated to 115 words (read the full abstract)

The explosion of Deep Learning (DL) added a boost to the already rapidly developing field of Computer Vision to such a point that vision-based tasks are now parts of our everyday lives. Applications such as image classification, photo stylization, or face recognition are nowadays pervasive, as evidenced by the advent of modern systems trivially integrated into mobile applications. In this thesis, we investigated and enhanced the visual counting task, which automatically estimates the number of objects in still images or video frames. Recently, due to the growing interest in it, several Convolutional Neural Network (CNN)-based solutions have been suggested by the scientific community. These artificial neural networks, inspired by the organization of the animal visual ... toggle 12 keywords

artificial intelligence – deep learning – computer vision – visual counting – object detection – data scarcity – synthetic data – domain adaptation – ai on embedded devices – convolutional neural networks – smart cities – computer vision in robotics

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